Liquid-biopsy proteomics combined with AI identifies cellular drivers of eye aging and disease in vivo.

Single-cell analysis in living humans is essential for understanding disease mechanisms, but it is impractical in non-regenerative organs, such as the eye and brain, because tissue biopsies would cause serious damage. We resolve this problem by integrating proteomics of liquid biopsies with single-cell transcriptomics from all known ocular cell types to trace the cellular origin of 5,953 proteins detected in the aqueous humor. We identified hundreds of cell-specific protein markers, including for individual retinal cell types. Surprisingly, our results reveal that retinal degeneration occurs in Parkinson's disease, and the cells driving diabetic retinopathy switch with disease stage. Finally, we developed artificial intelligence (AI) models to assess individual cellular aging and found that many eye diseases not associated with chronological age undergo accelerated molecular aging of disease-specific cell types. Our approach, which can be applied to other organ systems, has the potential to transform molecular diagnostics and prognostics while uncovering new cellular disease and aging mechanisms.

Patient Personality and Illness Perceptions in Relation to Follow-Up Appointment Adherence in Neuro-Ophthalmology.

BACKGROUND: Improving patient attendance at medical follow-up visits may have a notable impact on disease and overall health outcomes. Understanding factors contributing to poor attendance is important for identifying at-risk patients and designing interventions to improve clinical outcomes. Our objective was to identify personality and illness perception factors associated with attendance at recommended follow-up visits in a neuro-ophthalmology practice. METHODS: New or established patients (≥18 years) with scheduled neuro-ophthalmology (study) or glaucoma (comparison) appointments at a tertiary care academic medical center completed the Brief Illness Perception Questionnaire and Ten-Item Personality Inventory. Physician recommendations made during the visit were recorded (medications, referrals, follow-up, testing, and procedures). A chart review was performed 18 months after enrollment to assess attendance at follow-up appointment and adherence with other physician recommendations. Multiple variable logistic regression models studied associations between follow-up appointment attendance and demographic factors, appointment factors, and survey responses. RESULTS: Among 152 respondents (97% response rate (152 of 157), aged 19-97 years, 58% female, 34% new, 80 neuro-ophthalmology, 72 glaucoma), neuro-ophthalmology subjects were younger, more likely to be White, non-Hispanic, female and new to the practice than subjects with glaucoma. They reported higher emotional impact, identity, and consequences related to their illness (P = 0.001-0.03). Neuro-ophthalmology physician recommendations included more referrals to other services (17.5% vs 1.4%, P = 0.001, chi-square) and more radiology studies (15% vs 0%, P = 0.001, chi-square), but fewer follow-up visits (75% vs 97%, P < 0.0005, chi-square). Among those with recommended follow-up visits, neuro-ophthalmology subjects had lower rates of on-time appointment attendance (55% vs 77%, P = 0.009, chi-square). In a multiple variable model, on-time follow-up attendance was associated with shorter recommended follow-up interval (≤90 days, P < 0.0005), established (vs new) patient status at enrollment visit (P = 0.04), and glaucoma (P = 0.08), but not subject demographics, illness perception, or personality factors. CONCLUSIONS: Patient demographics, illness perception, and personality traits were not associated with follow-up appointment attendance and therefore unlikely to be useful for identifying patients at risk of being lost to follow-up. New neuro-ophthalmology patients with a follow-up recommended ≥90 days in advance may benefit from targeted interventions to improve follow-up appointment adherence.

Efficacy of a Deep Learning System for Detecting Glaucomatous Optic Neuropathy Based on Color Fundus Photographs.

PURPOSE: To assess the performance of a deep learning algorithm for detecting referable glaucomatous optic neuropathy (GON) based on color fundus photographs. DESIGN: A deep learning system for the classification of GON was developed for automated classification of GON on color fundus photographs. PARTICIPANTS: We retrospectively included 48 116 fundus photographs for the development and validation of a deep learning algorithm. METHODS: This study recruited 21 trained ophthalmologists to classify the photographs. Referable GON was defined as vertical cup-to-disc ratio of 0.7 or more and other typical changes of GON. The reference standard was made until 3 graders achieved agreement. A separate validation dataset of 8000 fully gradable fundus photographs was used to assess the performance of this algorithm. MAIN OUTCOME MEASURES: The area under receiver operator characteristic curve (AUC) with sensitivity and specificity was applied to evaluate the efficacy of the deep learning algorithm detecting referable GON. RESULTS: In the validation dataset, this deep learning system achieved an AUC of 0.986 with sensitivity of 95.6% and specificity of 92.0%. The most common reasons for false-negative grading (n = 87) were GON with coexisting eye conditions (n = 44 [50.6%]), including pathologic or high myopia (n = 37 [42.6%]), diabetic retinopathy (n = 4 [4.6%]), and age-related macular degeneration (n = 3 [3.4%]). The leading reason for false-positive results (n = 480) was having other eye conditions (n = 458 [95.4%]), mainly including physiologic cupping (n = 267 [55.6%]). Misclassification as false-positive results amidst a normal-appearing fundus occurred in only 22 eyes (4.6%). CONCLUSIONS: A deep learning system can detect referable GON with high sensitivity and specificity. Coexistence of high or pathologic myopia is the most common cause resulting in false-negative results. Physiologic cupping and pathologic myopia were the most common reasons for false-positive results.

Institutionalizing healthcare hackathons to promote diversity in collaboration in medicine.

BACKGROUND: Medical students and healthcare professionals can benefit from exposure to cross-disciplinary teamwork and core concepts of medical innovation. Indeed, to address complex challenges in patient care, diversity in collaboration across medicine, engineering, business, and design is critical. However, a limited number of academic institutions have established cross-disciplinary opportunities for students and young professionals within these domains to work collaboratively towards diverse healthcare needs. METHODS: Drawing upon best practices from computer science and engineering, healthcare hackathons bring together interdisciplinary teams of students and professionals to collaborate, brainstorm, and build solutions to unmet clinical needs. Over the course of six months, a committee of 20 undergraduates, medical students, and physician advisors organized Stanford University's first healthcare hackathon (November 2016). Demographic data from initial applications were supplemented with responses from a post-hackathon survey gauging themes of diversity in collaboration, professional development, interest in medical innovation, and educational value. In designing and evaluating the event, the committee focused on measurable outcomes of diversity across participants (skillset, age, gender, academic degree), ideas (clinical needs), and innovations (projects). RESULTS: Demographic data (n = 587 applicants, n = 257 participants) reveal participants across diverse academic backgrounds, age groups, and domains of expertise were in attendance. From 50 clinical needs presented representing 19 academic fields, 40 teams ultimately formed and submitted projects spanning web (n = 13) and mobile applications (n = 13), artificial intelligence-based tools (n = 6), and medical devices (n = 3), among others. In post-hackathon survey responses (n = 111), medical students and healthcare professionals alike noted a positive impact on their ability to work in multidisciplinary teams, learn from individuals of different backgrounds, and address complex healthcare challenges. CONCLUSIONS: Healthcare hackathons can encourage diversity across individuals, ideas, and projects to address clinical challenges. By providing an outline of Stanford's inaugural event, we hope more universities can adopt the healthcare hackathon model to promote diversity in collaboration in medicine.

An Extended Hackathon Model for Collaborative Education in Medical Innovation.

To support the next generation of healthcare innovators - whether they be engineers, designers, clinicians, or business experts by training - education in the emerging field of medical innovation should be made easily and widely accessible to undergraduate students, graduate students, and young professionals, early in their careers. Currently, medical innovation curricula are taught through semester-long courses or year-long fellowships at a handful of universities, reaching only a limited demographic of participants. This study describes the structure and preliminary outcomes of a 1-2 week "extended hackathon" course that seeks to make medical innovation education and training more accessible and easily adoptable for academic medical centers. Eight extended hackathons were hosted in five international locations reaching 245 participants: Beijing (June 2015 and August 2016), Hong Kong (June 2016, 2017, and 2018), Curitiba (July 2016), Stanford (October 2017), and São Paulo (May 2018). Pre- and post-hackathon surveys asking respondents to self-assess their knowledge in ten categories of medical innovation were administered to quantify the perceived degree of learning. Participants hailed from a diverse range of educational backgrounds, domains of expertise, and academic institutions. On average, respondents (n = 161) saw a greater than twofold increase (114.1%, P < 0.001) from their pre- to post-hackathon scores. In this study, the extended hackathon is presented as a novel educational model to teach undergraduate and graduate students a foundational skillset for medical innovation. Participants reported gaining significant knowledge across all ten categories assessed. To more robustly assess the educational value of extended hackathons, a standardized assessment for medical innovation knowledge needs to be developed, and a larger sample size of participants surveyed.

Correction to: An Extended Hackathon Model for Collaborative Education in Medical Innovation.

We append two additional funders to our acknowledgments.

Serial Spectral-Domain Optical Coherence Tomography Findings in Acute Retinal Pigment Epitheliitis and the Correlation to Visual Acuity.

PURPOSE: To evaluate the features of acute retinal pigment epitheliitis (ARPE) at onset and in the course of recovery by serial spectral-domain optical coherence tomography (SD OCT) and the correlation to visual acuity (VA). DESIGN: Retrospective cohort study. PARTICIPANTS: Consecutive patients with ARPE. METHODS: A review of medical records was performed. MAIN OUTCOME MEASURES: Integrity of SD OCT retinal bands at onset and in the course of disease, time required to achieve each retinal band restoration, corresponding VA change, and final VA. RESULTS: Four patients were included. Initial SD OCT showed a dome-shaped hyper-reflective lesion at the photoreceptor outer segment layer disrupting the ellipsoid zone (EZ) and interdigitation zone (IZ) (100%). In the early phase, there was also upward displacement of the external limiting membrane (ELM) and mild transient thickening of the retinal pigment epithelium (RPE)/Bruch's complex (Bc). Acute retinal pigment epitheliitis resolved in a sequence of (1) a decrease in height of SD OCT hyper-reflective lesion and the upwardly displaced ELM returning to its normal position with irregularity; (2) complete disappearance of the hyper-reflective lesion; (3) restoration of ELM; (4) restoration of EZ; and (5) restoration of IZ. The average time to restore ELM, EZ, and IZ was 4.3±5.2, 7.3±7.2, and 12.5±12.4 weeks, respectively, and the corresponding logarithm of the minimum angles of resolution (logMAR) VAs were 0.24±0.23, 0.09±0.07, and 0.05±0.06, respectively. Visual acuity improved when IZ was restored. CONCLUSIONS: Early SD OCT revealed an inflammatory lesion in the photoreceptor outer segment layer displacing ELM. The RPE was involved only mildly and transiently. Recovery occurred in a sequence of ELM, EZ, and IZ restoration, and VA improved when the IZ was restored. These features suggested that the IZ (i.e., the contact between photoreceptors and RPE) is the primary site of inflammation in ARPE.

Specific Location of Disc Hemorrhage is Linked to Nerve Fiber Layer Defects.

PURPOSE: To investigate the relationship between retinal nerve fiber layer (RNFL) defects and the quadrant and proximal location of disc hemorrhages (DHs) in a large population examined for health screening. METHODS: A total of 168,044 subjects older than 20 years underwent a single screening ophthalmic examination with color fundus photography as part of a comprehensive health screening program. The presence and location of DHs and RNFL defects were assessed. The DH locations were defined according to the quadrant location (inferotemporal, superotemporal, inferonasal, or superonasal) and the most proximal end of DHs relative to the disc center (cup base, cup margin, disc rim, or extrapapillary region). Using these two location descriptors as independent variables, a logistic regression analysis was conducted to explore the effects of DH location on RNFL defects. RESULTS: Two hundred twenty-six eyes had DH and 120 (53.1%) of them had RNFL defects. After adjusting for proximal location, DHs located in the inferotemporal quadrant accompanied RFNL defects 12 times more frequently than those in the superonasal quadrant (odds ratio [OR], 11.81; P = .004). Conversely, after adjusting for quadrant location, the ORs for an associated RNFL defect were 3.73 (P < .001), 16.54 (P < .001), and 8.91 (P = .002) for DHs with the proximal end at the disc rim, cup margin, and cup base, respectively. CONCLUSIONS: Among the four quadrants and four proximal locations, DHs were identified most frequently in the inferotemporal quadrant and outside the disc, respectively. Some DH locations, such as the inferotemporal quadrant and the cup margin, were associated with RNFL defects, whereas others were not.

Factors Associated with Patient Press Ganey Satisfaction Scores for Ophthalmology Patients.

PURPOSE: To determine which metrics from the Press Ganey patient satisfaction survey best correlate with "likelihood to recommend" among patients in an academic tertiary medical center practice setting. DESIGN: Cross-sectional study. PARTICIPANTS: Over a 3-month period, patients presenting to an academic practice who agreed to participate were enrolled in the study if they met the following entry criteria: (1) age ≥18 years, (2) ability to read and speak English, and (3) followed in this practice between 4 months and 4 years. A total of 196 patients were recruited. METHODS: A 26-item abridged version of the Press Ganey survey typically distributed to patients via mail or e-mail after visiting the Stanford University Hospital was administered privately to each eligible patient of 2 different attending clinics at the conclusion of his or her visit. The 26 survey items were not modified for the purposes of the study and were administered such that participants could not be individually identified. The arithmetic mean score for the item "Likelihood of your recommending our practice to others" was calculated by assigning a value (0-100) to the Likert value associated with survey responses and correlated with the 25 other items using the differences in the mean scores. MAIN OUTCOME MEASURES: Response to survey items graded on a 1 to 5 standard Likert scale. RESULTS: The weighted mean patient survey score for the "likelihood to recommend" item for the junior faculty member was 95.9% and for the senior faculty member was 94.5%, respectively. For the remaining 25 items, "Amount of time the care provider spent with you" (Diff[1-2]=1.03; P < 0.0001) and "Ease of scheduling your appointment" (Diff[1-2]=0.99; P < 0.0001) best correlated with likelihood to recommend. In contrast, "Friendliness/courtesy of the care provider" (Diff[1-2]=0.29; P = 0.0045) correlated least with likelihood to recommend. Stratification based on provider did not affect the study results. CONCLUSIONS: The perception of time spent with the practitioner and ease of appointment scheduling are the 2 variables that best correlate with patients recommending their ophthalmologists to other prospective patients.

SMARTPHONE-BASED DILATED FUNDUS PHOTOGRAPHY AND NEAR VISUAL ACUITY TESTING AS INEXPENSIVE SCREENING TOOLS TO DETECT REFERRAL WARRANTED DIABETIC EYE DISEASE.

PURPOSE: To compare clinical assessment of diabetic eye disease by standard dilated examination with data gathered using a smartphone-based store-and-forward teleophthalmology platform. METHODS: 100 eyes of 50 adult patients with diabetes from a health care safety-net ophthalmology clinic. All patients underwent comprehensive ophthalmic examination. Concurrently, a smartphone was used to estimate near visual acuity and capture anterior and dilated posterior segment photographs, which underwent masked, standardized review. Quantitative comparison of clinic and smartphone-based data using descriptive, kappa, Bland-Altman, and receiver operating characteristic analyses was performed. RESULTS: Smartphone visual acuity was successfully measured in all eyes. Anterior and posterior segment photography was of sufficient quality to grade in 96 and 98 eyes, respectively. There was good correlation between clinical Snellen and smartphone visual acuity measurements (rho = 0.91). Smartphone-acquired fundus photographs demonstrated 91% sensitivity and 99% specificity to detect moderate nonproliferative and worse diabetic retinopathy, with good agreement between clinic and photograph grades (kappa = 0.91 ± 0.1, P < 0.001; AUROC = 0.97, 95% confidence interval, 0.93-1). CONCLUSION: The authors report a smartphone-based telemedicine system that demonstrated sensitivity and specificity to detect referral-warranted diabetic eye disease as a proof-of-concept. Additional studies are warranted to evaluate this approach to expanding screening for diabetic retinopathy.

Diagnostic performance of optical coherence tomography ganglion cell--inner plexiform layer thickness measurements in early glaucoma.

PURPOSE: To evaluate the glaucoma diagnostic performance of ganglion cell inner-plexiform layer (GCIPL) parameters used individually and in combination with retinal nerve fiber layer (RNFL) or optic nerve head (ONH) parameters measured with Cirrus HD-OCT (Carl Zeiss Meditec, Inc, Dublin, CA). DESIGN: Prospective cross-sectional study. PARTICIPANTS: Fifty patients with early perimetric glaucoma and 49 age-matched healthy subjects. METHODS: Three peripapillary RNFL and 3 macular GCIPL scans were obtained in 1 eye of each participant. A patient was considered glaucomatous if at least 2 of the 3 RNFL or GCIPL scans had the average or at least 1 sector measurement flagged at 1% to 5% or less than 1%. The diagnostic performance was determined for each GCIPL, RNFL, and ONH parameter as well as for binary or-logic and and-logic combinations of GCIPL with RNFL or ONH parameters. MAIN OUTCOME MEASURES: Sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR). RESULTS: Among GCIPL parameters, the minimum had the best diagnostic performance (sensitivity, 82.0%; specificity, 87.8%; PLR, 6.69; and NLR, 0.21). Inferior quadrant was the best RNFL parameter (sensitivity, 74%; specificity, 95.9%; PLR, 18.13; and NLR, 0.27), as was rim area (sensitivity, 68%; specificity, 98%; PLR, 33.3; and NLR, 0.33) among ONH parameters. The or-logic combination of minimum GCIPL and average RNFL provided the overall best diagnostic performance (sensitivity, 94%; specificity, 85.7%; PRL, 6.58; and NLR, 0.07) as compared with the best RNFL, best ONH, and best and-logic combination (minimum GCIPL and inferior quadrant RNFL; sensitivity, 64%; specificity, 100%; PLR, infinity; and NPR, 0.36). CONCLUSIONS: The binary or-logic combination of minimum GCIPL and average RNFL or rim area provides better diagnostic performances than those of and-logic combinations or best single GCIPL, RNFL, or ONH parameters. This finding may be clinically valuable for the diagnosis of early glaucoma.

Glaucoma Home Self-Testing Using VR Visual Fields and Rebound Tonometry Versus In-Clinic Perimetry and Goldmann Applanation Tonometry: A Pilot Study.

Purpose: This pilot study aimed to assess the feasibility, accuracy, and repeatability of unsupervised, at-home, multi-day glaucoma testing using the Olleyes VisuALL Virtual Reality Platform (VRP) and the iCare HOME handheld self-tonometer. Methods: Participants were trained to use two U.S. Food and Drug Administration-registered or approved devices before conducting self-tests at home over 3 consecutive days. The iCare HOME intraocular pressure (IOP) measurements were collected four times daily per eye, and VRP visual field tests were performed once daily. The results were compared with one in-clinic Humphrey Field Analyzer (HFA) visual field test performed on the day of device training, iCare HOME measurements by the trainer, and the last five Goldmann applanation tonometer (GAT) results. Results: Of 15 enrolled participants, nine of them (60%) completed the study. The six excluded participants could not self-measure using iCare HOME. There was significant correlation between the average mean deviation (MD) values of the at-home VRP tests and in-clinic HFA test (r2 = 0.8793, P < 0.001). Additionally, the average of the sensitivities in five of six Garway-Heath sectors were significantly correlated. VRP test duration was also shorter than in-clinic HFA testing (P < 0.001). Finally, at-home tonometry yielded statistically similar values compared to trainer-obtained iCare HOME values. The mean and range of at-home tonometry were also statistically similar to those for in-clinic GAT, but at-home tonometry demonstrated higher maximum IOP values (P = 0.0429). Conclusions: Unsupervised, at-home, multi-day glaucoma testing using two devices resulted in the capture of higher maximum IOPs than in the clinic and good MD correlation of VRP with HFA. However, 40% of participants could not self-measure IOP using iCare HOME. Translational Relevance: The study findings suggest that at-home remote glaucoma monitoring correlates with in-office testing and could provide additional information for glaucoma management, although patients had more difficulty with the iCare HOME than the VRP.

Comparing a Head-Mounted Smartphone Visual Field Analyzer to Standard Automated Perimetry in Glaucoma: A Prospective Study.

PRCIS: Wang et al compare an FDA-registered head-mounted smartphone device (PalmScan VF2000) with standard automated perimetry (SAP) in glaucoma patients and find that the head-mounted device may not fully recapitulate SAP testing. PURPOSE: This study prospectively compared visual field testing using the PalmScan VF2000 Visual Field Analyzer, a head-mounted smartphone device, with standard automated perimetry (SAP). METHODS: Patients with glaucoma undergoing Humphrey Field Analyzer SAP testing were asked to complete in-office PalmScan testing using a Samsung S5 smartphone in a virtual reality-style headset. Glaucoma severity was defined as SAP mean deviation (MD) >-6 dB for mild, between -6 and -12 dB for moderate, and <-12 dB for severe. Global parameters MD and pattern SD from PalmScan and SAP were compared using t -tests and Bland-Altman analyses. Bland-Altmann analyses of PalmScan and SAP MD were conducted for the superonasal, superotemporal, inferonasal, and inferotemporal visual field quadrants. The repeatability of PalmScan was assessed using Spearman's correlations and intraclass correlation coefficients (ICCs). RESULTS: Fifty-one patients (51 eyes) completed both SAP and PalmScan testing and met the criteria for analysis. Compared with SAP, global MD and pattern SD measurements from PalmScan differed by an average of +0.62±0.26 dB (range: -3.25 to +4.60 dB) and -1.00±0.24 dB (range: -6.03 to +2.77 dB), respectively, while MD scores from individual visual field quadrants differed by as much as -6.58 to +11.43 dB. The agreement between PalmScan and SAP in classifying glaucoma severity was 86.3% across all eyes. PalmScan and SAP identified the same quadrant as having the worst visual field defect in 66.7% of eyes. CONCLUSIONS: Despite advantages in cost and accessibility, the PalmScan head-mounted perimetry device may not be able to fully recapitulate SAP testing.

Clinical spectrum and possible pathogenesis of progressive outer retinal necrosis.

OBJECTIVE: Progressive outer retinal necrosis (PORN) is an alphaherpesvirus-caused panuveitis with devastating consequences for the eye. Our study aims to describe new findings in the clinical spectrum and propose a mechanism for the pathogenesis of PORN. METHODS: Observational, consecutive case series. Seven eyes from five patients diagnosed with PORN were enrolled. Detailed case histories, ocular examination findings and multimodal images of retina were collected. Optic nerve and brain imaging were obtained by MRI. RESULTS: All eyes were confirmed human alphaherpesviruses positive in ocular fluid by qPCR. Optic nerve oedema was observed on MRI in all eyes. A relative afferent pupillary defect was recorded in the affected eye for the unilateral cases. Two patients with unilateral involvement had a history of viral encephalitis and focal encephalomalacia found in the temporal lobe on brain MRI. The affected eyes were characterised by sensory retinal necrosis sparing retinal pigment epithelium, starting at the end of the retinal nerve fibre (horizontal raphe or peripheral area of the retina) and progressing rapidly along the nerve fibre. The wall of the retinal artery and vein was destroyed, resulting in blood flow interruption on fluorescein angiography and retinal haemorrhages along the large vessels. CONCLUSIONS: Combination the neurotropic characteristics of alphaherpesviruses and the signs of PORN, we hypothesised that the reactivated PORN virus originated from the lateral geniculate nucleus, then propagated along the optic nerve and was released at the terminals, causing necrosis of the entire sensory retina rather than just affecting the outer segment.

Understanding natural language: Potential application of large language models to ophthalmology.

Large language models (LLMs), a natural language processing technology based on deep learning, are currently in the spotlight. These models closely mimic natural language comprehension and generation. Their evolution has undergone several waves of innovation similar to convolutional neural networks. The transformer architecture advancement in generative artificial intelligence marks a monumental leap beyond early-stage pattern recognition via supervised learning. With the expansion of parameters and training data (terabytes), LLMs unveil remarkable human interactivity, encompassing capabilities such as memory retention and comprehension. These advances make LLMs particularly well-suited for roles in healthcare communication between medical practitioners and patients. In this comprehensive review, we discuss the trajectory of LLMs and their potential implications for clinicians and patients. For clinicians, LLMs can be used for automated medical documentation, and given better inputs and extensive validation, LLMs may be able to autonomously diagnose and treat in the future. For patient care, LLMs can be used for triage suggestions, summarization of medical documents, explanation of a patient's condition, and customizing patient education materials tailored to their comprehension level. The limitations of LLMs and possible solutions for real-world use are also presented. Given the rapid advancements in this area, this review attempts to briefly cover many roles that LLMs may play in the ophthalmic space, with a focus on improving the quality of healthcare delivery.

Repeatability of a Virtual Reality Headset Perimeter in Glaucoma and Ocular Hypertensive Patients.

Purpose: The VisuALL S is an automated, static threshold, virtual reality-based perimeter for mobile evaluation of the visual field. We examined same-day and 3-month repeatability. Methods: Adult participants with a diagnosis of glaucoma or ocular hypertension underwent two VisuALL 24-2 Normal T- Full threshold strategy tests at baseline and one additional exam at 3 months for each eligible eye. Spearman, intraclass correlation coefficients (ICCs), and Bland-Altman plots were used to assess the correlation of individual point sensitivities and mean deviation (MD) among three tests. Results: Eighty-eight eyes (44 participants) were included. Average age was 68.1 ± 14.3 years, and 60.7% were male. VisuALL MD was highly correlated between tests (intravisit: r = 0.89, intervisit: r = 0.82; P < 0.001 for both). Bland-Altman analysis showed an average difference in intravisit MD of -0.67 dB (95% confidence interval [CI], -6.04 to 4.71 dB) and -0.15 dB (95% CI, -8.04 to 7.73 dB) for intervisit exams. Eight-five percent of pointwise intravisit ICCs were above 0.75 (range, 0.63 to 0.93), and 65% of pointwise intervisit ICCs were above 0.75 (range, 0.55 to 0.91). Conclusions: VisuALL demonstrated high correlation of MD between tests and good repeatability for individual point sensitivities among three tests in 3 months, except at the points around the blind spot and superiorly. Translational Relevance: The preliminary reproducibility results for VisuALL are encouraging. Its portable design makes it a potentially useful tool for patients with glaucoma, enabling more frequent assessments both at home and in clinical settings.

Using Electronic Health Record Data to Determine the Safety of Aqueous Humor Liquid Biopsies for Molecular Analyses.

Purpose: Knowing the surgical safety of anterior chamber liquid biopsies will support the increased use of proteomics and other molecular analyses to better understand disease mechanisms and therapeutic responses in patients and clinical trials. Manual review of operative notes from different surgeons and procedures in electronic health records (EHRs) is cumbersome, but free-text software tools could facilitate efficient searches. Design: Retrospective case series. Participants: A total of 1418 aqueous humor liquid biopsies from patients undergoing intraocular surgery. Methods: Free-text EHR searches were performed using the Stanford Research Repository cohort discovery tool to identify complications associated with anterior chamber paracentesis and subsequent endophthalmitis. Complications of the surgery unrelated to the biopsy were not reviewed. Main Outcome Measures: Biopsy-associated intraoperative complications and endophthalmitis. Results: A total of 1418 aqueous humor liquid biopsies were performed by 17 experienced surgeons. EHR free-text searches were 100% error-free for surgical complications, >99% for endophthalmitis (<1% false positive), and >93.6% for anesthesia type, requiring manual review for only a limited number of cases. More than 85% of cases were performed under local anesthesia without ocular muscle akinesia. Although the most common indication was cataract (50.1%), other diagnoses included glaucoma, diabetic retinopathy, uveitis, age-related macular degeneration, endophthalmitis, retinitis pigmentosa, and uveal melanoma. A 50- to 100-µL sample was collected in all cases using either a 30-gauge needle or a blunt cannula via a paracentesis. The median follow-up was >7 months. There was only one minor complication (0.07%) identified: a case of a small tear in Descemet membrane without long-term sequelae. No other complications occurred, including other corneal injuries, lens or iris trauma, hyphema, or suprachoroidal hemorrhage. There was no case of postoperative endophthalmitis. Conclusions: Anterior chamber liquid biopsy during intraocular surgery is a safe procedure and may be considered for large-scale collection of aqueous humor samples for molecular analyses. Free-text EHR searches are an efficient approach to reviewing intraoperative procedures. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Myopia and glaucoma: diagnostic and therapeutic challenges.

PURPOSE OF REVIEW: There is strong epidemiologic evidence linking myopia with glaucomatous disease, but a myopic optic nerve can pose significant challenges with regard to making the correct diagnosis of glaucoma. This review provides an overview of these diagnostic and therapeutic challenges with a particular focus on how the growing prevalence of myopia among specific populations may impact such therapy. RECENT FINDINGS: For a given individual, the link between myopia and glaucoma remains murky in many circumstances, largely because of the fact that it is difficult to separate out myopia-related structural and functional abnormalities from 'true' glaucomatous changes. Using optical coherence tomography (OCT) imaging, myopia has been found to be associated with temporal displacement and thinning of the superior and inferior nerve fiber layer bundles. In particular, sequential generations of 'Asian' ethnicities have been noted to demonstrate increasing rates of high myopia at earlier ages, sometimes with associated visual field defects at normal intraocular pressures. As is the case with any progressive condition, it is often not possible to distinguish glaucomatous from nonglaucomatous disease based on a single examination, and thus follow-up with OCT or perimetry from an established baseline is useful. SUMMARY: Although myopia is a known risk factor for glaucoma, it may also result in structural and functional defects that cannot be distinguished from those caused by glaucoma based solely on cross-sectional information. Longitudinal observation may be necessary to distinguish among the multiple effects of myopia on the optic nerve and the natural history of glaucoma, which may vary substantially amongst those who are affected.

Real-world agreement of same-visit Tono-Pen vs Goldmann applanation intraocular pressure measurements using electronic health records.

Purpose: To compare intraocular pressure (IOP) obtained with Tono-Pen (TP) and Goldmann applanation (GAT) using large-scale electronic health records (EHR). Design: Retrospective cohort study. Methods: A single pair of eligible TP/GAT IOP readings was randomly selected from the EHR for each ophthalmology patient at an academic ophthalmology center (2013-2022), yielding 4550 eligible measurements. We used Bland-Altman analysis to describe agreement between TP/GAT IOP differences and mean IOP measurements. We also used multivariable logistic regression to identify factors associated with different IOP readings in the same eye, including demographics, glaucoma diagnosis, and central corneal thickness (CCT). Primary outcome metrics were discrepant measurements between TP and GAT as defined by two methods: Outcome A (normal TP despite elevated GAT measurements), and Outcome B (TP and GAT IOP differences ≥6 mmHg). Result: The mean TP/GAT IOP difference was 0.15 mmHg ( ± 5.49 mmHg 95% CI). There was high correlation between the measurements (r = 0.790, p < 0.001). We found that TP overestimated pressures at IOP <16.5 mmHg and underestimated at IOP >16.5 mmHg (Fig. 4). Discrepant measurements accounted for 2.6% (N = 116) and 5.2% (N = 238) for outcomes A and B respectively. Patients with thinner CCT had higher odds of discrepant IOP (OR 0.88 per 25 µm increase, CI [0.84-0.92], p < 0.0001; OR 0.88 per 25 µm increase, CI [0.84-0.92], p < 0.0001 for outcomes A and B respectively). Conclusion: In a real-world academic practice setting, TP and GAT IOP measurements demonstrated close agreement, although 2.6% of measurements showed elevated GAT IOP despite normal TP measurements, and 5.2% of measurements were ≥6 mmHg apart.

Comparison of Ophthalmologist and Large Language Model Chatbot Responses to Online Patient Eye Care Questions.

Importance: Large language models (LLMs) like ChatGPT appear capable of performing a variety of tasks, including answering patient eye care questions, but have not yet been evaluated in direct comparison with ophthalmologists. It remains unclear whether LLM-generated advice is accurate, appropriate, and safe for eye patients. Objective: To evaluate the quality of ophthalmology advice generated by an LLM chatbot in comparison with ophthalmologist-written advice. Design, Setting, and Participants: This cross-sectional study used deidentified data from an online medical forum, in which patient questions received responses written by American Academy of Ophthalmology (AAO)-affiliated ophthalmologists. A masked panel of 8 board-certified ophthalmologists were asked to distinguish between answers generated by the ChatGPT chatbot and human answers. Posts were dated between 2007 and 2016; data were accessed January 2023 and analysis was performed between March and May 2023. Main Outcomes and Measures: Identification of chatbot and human answers on a 4-point scale (likely or definitely artificial intelligence [AI] vs likely or definitely human) and evaluation of responses for presence of incorrect information, alignment with perceived consensus in the medical community, likelihood to cause harm, and extent of harm. Results: A total of 200 pairs of user questions and answers by AAO-affiliated ophthalmologists were evaluated. The mean (SD) accuracy for distinguishing between AI and human responses was 61.3% (9.7%). Of 800 evaluations of chatbot-written answers, 168 answers (21.0%) were marked as human-written, while 517 of 800 human-written answers (64.6%) were marked as AI-written. Compared with human answers, chatbot answers were more frequently rated as probably or definitely written by AI (prevalence ratio [PR], 1.72; 95% CI, 1.52-1.93). The likelihood of chatbot answers containing incorrect or inappropriate material was comparable with human answers (PR, 0.92; 95% CI, 0.77-1.10), and did not differ from human answers in terms of likelihood of harm (PR, 0.84; 95% CI, 0.67-1.07) nor extent of harm (PR, 0.99; 95% CI, 0.80-1.22). Conclusions and Relevance: In this cross-sectional study of human-written and AI-generated responses to 200 eye care questions from an online advice forum, a chatbot appeared capable of responding to long user-written eye health posts and largely generated appropriate responses that did not differ significantly from ophthalmologist-written responses in terms of incorrect information, likelihood of harm, extent of harm, or deviation from ophthalmologist community standards. Additional research is needed to assess patient attitudes toward LLM-augmented ophthalmologists vs fully autonomous AI content generation, to evaluate clarity and acceptability of LLM-generated answers from the patient perspective, to test the performance of LLMs in a greater variety of clinical contexts, and to determine an optimal manner of utilizing LLMs that is ethical and minimizes harm.